Casadi Interface for Optimum experimental design and Parameter Estimation and Identification Applications

casiopeia holds a user-friendly environment for optimum experimental design and parameter estimation and identification applications. It does so by providing Python classes that can be initialized with the problem specifications, while the computations can then easily be performed using the available class functions.

casiopeia uses the optimization framework CasADi to solve the resulting optimization problems.

Note

casiopeia makes use of the optimization framework CasADi. For casiopeia to work, you need CasADi version = 3.1.0 to be installed on your system, otherwise the installation of casiopeia will abort or not might work as expected. Also, casiopeia is available only for Python 2.7.

In the following sections, you will receive the information necessary to obtain, install and use casiopeia. If you encounter any problems using this software, please feel free to submit your errors with a description of how they occurred to adrian(dot)buerger(at)hs-karlsruhe(dot)de.

Contents

• 1. Get and install casiopeia
  • 1.1. Installation on Ubuntu 18.04
  • 1.2. Recommendations
• 2. Defining a system
• 3. System simulation
• 4. Parameter estimation
  • 4.1. Parameter estimation from single experiments
  • 4.2. Parameter estimation from multiple experiments
• 5. Optimum experimental design
  • 5.1. Optimum experimental design of single experiments
  • 5.2. Optimum experimental design of multiple experiments
• 6. Sample applications
  • 6.1. Parameter estimation for a Lotka-Volterra predator-prey-model
  • 6.2. Parameter estimation for a pendulum model
  • 6.3. Parameter estimation for a model race car
  • 6.4. Optimum experimental design for a model race car